What is the difference between a Hopfield Network and a Neural Network or a Perceptron?
Hopfield stores some predefined patterns (lower energy states) and when an non seen pattern is fed to the Hopfield net, it tries to find the closest match among the stored patterns. Hence the output of a Hopfield is always one of the predefined patterns which matches closely to the unseen input pattern.

This is not the case with Feed Forward Neural Nets (where no such predefined patterns are stored) and every input generates a corresponding output. Here (in Feedforward) the output is generated by a predefined function (which is self-adjusted during training session) where as in Hopfield predefined patterns are stored and outputted (no such functions exist).